Lingxiao Chen

@LingxiaoChen2

PhD student . Low back pain and spinal stenosis. Meta-analysis. Linked-data analysis. R.

Sydney, New South Wales
Vrijeme pridruživanja: lipanj 2018.

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  1. proslijedio/la je Tweet
    2. velj

    Since everyone's so read up on R0 (reproductive number) of diseases due to the now, thought I'd do a quick thread explaining herd immunity Both concepts are closely related!

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  2. proslijedio/la je Tweet
    3. velj

    “Whenever we conduct statistical analyses, we make assumptions. Arguably the most common assumption of all, however, is barely mentioned: we assume the measurement we get is exactly the same as whatever we are trying to measure”

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  3. proslijedio/la je Tweet
    3. velj

    New paper: Technology and Big Data Are Changing Economics by Janet Currie, Henrik Kleven & Esmée Zwiers "Event studies and bunching approaches are more recent...linked to the increased use of administrative data sources" Machine learning also on the rise

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  4. proslijedio/la je Tweet
    1. velj
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  5. proslijedio/la je Tweet
    21. sij

    An Introduction to Directed Acyclic Graphs • ggdag

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  6. proslijedio/la je Tweet
    25. sij

    Simulation models can be a useful way to combine what we think we know into a numeric summary, but that summary is only as good as our knowledge. If we have very little real knowledge, like with the new coronavirus, the summary can be very very wrong. Be patient & wait for data.

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  7. proslijedio/la je Tweet
    1. velj

    This is an important point for epidemiology too. Some of the questions we want to answer need complex methods, but many of our important questions could be answered much more easily if only we had the right, good quality data.

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  8. proslijedio/la je Tweet
    1. velj

    Can Confidence Intervals be Interpreted? | American Journal of Epidemiology | Oxford Academic

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  9. proslijedio/la je Tweet
    1. velj

    An important thread about panic, that it’s not typical or inevitable, how it’s fueled, and why it’s dangerous. Take a moment to read this 👇🏼

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  10. proslijedio/la je Tweet
    28. sij

    All this talk of a new virus can be scary, but there are plenty of things regular people can do to help prevent or stop an outbreak. To see how you can help, check out my new post: “A regular person’s guide to outbreak preparedness” 👇🏼

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  11. proslijedio/la je Tweet
    20. sij
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  12. proslijedio/la je Tweet
    20. sij

    thought of the day: Once you understand that optimum decision making is predictive (not retrospective) and needs utilities specified, you'll stop using sens/spec/ROC/confusion matrix:

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  13. proslijedio/la je Tweet
    16. sij

    If you’re struggling to know what to report when you haven’t used meta-analysis in a review, check out SWiM - Synthesis without meta-analysis (SWiM) in systematic reviews: reporting guideline

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  14. proslijedio/la je Tweet
    17. sij

    Use of E-values for addressing confounding in observational studies—an empirical assessment of the literature | International Journal of Epidemiology | Oxford Academic

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  15. proslijedio/la je Tweet
    17. sij

    Statistical inference for association studies using electronic health records: handling both selection bias and outcome misclassification | medRxiv

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  16. proslijedio/la je Tweet
    15. sij

    Causal Inference in Introductory Statistics Courses: Journal of Statistics Education: Vol 0, No ja

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  17. proslijedio/la je Tweet
    2. sij
    Odgovor korisnicima

    Most people are pretty burnt by the end of a PhD. A good post-doc can be rejuvenating or confirm it's not your cup of tea. If you're unsure, look for a post-doc that will be fun & give you time to breathe before deciding. Check out this from :

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  18. proslijedio/la je Tweet
    2. sij

    Happy New Year! To celebrate 2020, how about an ? Today, let’s talk about e-values and how to interpret them!

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  19. proslijedio/la je Tweet
    3. sij

    thought of the day: I don't seek someone's decision about whether it will rain today. I want Prob(rain) in playing the odds when considering an umbrella. Likewise, testing null hypotheses is far less useful than playing the odds of a treatment effect.

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  20. proslijedio/la je Tweet
    3. sij

    This thread nicely highlights something that’s always bothered me with AI vs doctor comparisons — when the gold standard is the doctors’ diagnoses, AI can at best only ever do par. If we want to move the needle, then we need to assess success on *outcomes* not diagnoses!

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